Energy-Efficient Databases using Sweet Spot Frequencies

Authors

Abstract

A common misconception is to equate software energy-efficiency to CPU performance. The rationale of this fallacy is that increasing CPU clock frequency involves a reduction of CPU usage in time and, hence, energy consumption. In this paper, we give empirical evidence for scenarios where a server is more energy-efficient when its CPU(s) operate(s) at a lower frequency than the maximum allowed frequency. Our approach uses a novel high-precision, fine-grained energy measurement infrastructure to investigate the energy (joules) consumed by three different sorting algorithms. Our experiments show the existence of algorithm sweet spots: CPU clock frequencies at which algorithms achieve the lowest energy consumption to complete the same computational task. To leverage these findings, we describe how a new kind of self-adaptive software applications can be engineered to increase their energy-efficiency.